Is it possible to group multiple columns individually without using union?

Question

Hi, if I have a table with a numebr of columns I want to group eg gender, nationality, age and I want to produce a summary such like:
Group Count
Male 10
Female 23
British 19
Irish 14
18 10
etc.
Or even better:
Group Count
Gender-Male 10
Gender-Female 23
Nationaility-British 19
Nationality-Irish 14
Age-18 10
Is this possible without using loads of unions? I just want to do this in the best, most efficient way as the table involved has >100 million rows.
Many thanks
Jen :)

Answer 1

May be this
--Test data
with t
as
select 'M' gender, 'INDIAN'  nationality, 25 age from dual union all
select 'M' gender, 'INDIAN'  nationality, 25 age from dual union all
select 'M' gender, 'INDIAN'  nationality, 30 age from dual union all
select 'M' gender, 'IRISH'   nationality, 30 age from dual union all
select 'M' gender, 'IRISH'   nationality, 40 age from dual union all
select 'F' gender, 'IRISH'   nationality, 40 age from dual union all
select 'F' gender, 'BRITISH' nationality, 50 age from dual union all
select 'F' gender, 'BRITISH' nationality, 50 age from dual union all
select 'F' gender, 'BRITISH' nationality, 45 age from dual union all
select 'F' gender, 'BRITISH' nationality, 45 age from dual
--Test Data Ends
-- Main Query
select decode(no, 1, 'Gender-', 2, 'Nationality-', 3, 'Age-') || decode(no, 1, gender, 2, nationality, 3, to_char(age)) val,
       count(*) cnt
  from t
cross join (select level no from dual connect by level <= 3)
group by no, decode(no, 1, gender, 2, nationality, 3, to_char(age))
order by no;
VAL                                                  CNT
Gender-F                                               5
Gender-M                                               5
Nationality-BRITISH                                    4
Nationality-INDIAN                                     3
Nationality-IRISH                                      3
Age-25                                                 2
Age-30                                                 2
Age-40                                                 2
Age-45                                                 2
Age-50                                                 2
10 rows selected